Triple

T13835389
Position Surface form Disambiguated ID Type / Status
Subject Eric Douglas E332511 entity
Predicate hasRelative P367 FINISHED
Object Diana Dill E187145 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Diana Dill | Statement: [Eric Douglas, hasRelative, Diana Dill]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diana Dill
Context triple: [Eric Douglas, hasRelative, Diana Dill]
  • A. Diana Dill chosen
    Diana Dill was a Bermudian-born actress known for her film and television work and as the mother of actor Michael Douglas.
  • B. Diane Nelson
    Diane Nelson is an American media executive best known for serving as president of DC Entertainment and overseeing the DC Comics brand at Warner Bros.
  • C. Elizabeth Dailey
    Elizabeth Dailey is known primarily as the spouse of American actor and dancer Dan Dailey.
  • D. Judi Farr
    Judi Farr was an Australian actress known for her extensive work in theatre, film, and television, including prominent roles in classic Australian TV comedies and dramas.
  • E. Diane Ayres
    Diane Ayres is an American writer and editor known for her work in fiction and essays, often exploring contemporary relationships and women's experiences.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d81c5ae7c88190b0dd41bdafeb5999 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de029b352081909605baaedc336213 completed April 14, 2026, 9:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd6474da3081909be6b892ef8cc73e completed May 8, 2026, 4:20 a.m.
Created at: April 9, 2026, 10:13 p.m.